Next generation electromagnetic optimization with the covariance matrix adaptation evolutionary strategy

M. D. Gregory, D. H. Werner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Classical evolutionary strategies such as the genetic algorithm and particle swarm technique have long been the most called upon methods for optimization of electromagnetic design problems. Due to their capability for robust global search and their ease of implementation, they have been fruitfully applied to the design of antennas, arrays, frequency selective surfaces, metamaterials and other electromagnetic devices. Since then, many new optimization techniques have been developed that often allow more complex design problems to be tackled, or reduce the time needed to optimize the problems of the past. One algorithm found particularly effective is the covariance matrix adaptation evolutionary strategy (CMA-ES). The operation of CMA-ES will be covered in detail here. Additionally, the powerful performance of the technique when confronted with several different design problems and test functions will be demonstrated.

Original languageEnglish (US)
Title of host publication2011 IEEE International Symposium on Antennas and Propagation - Proceedings
Pages2423-2426
Number of pages4
DOIs
StatePublished - Nov 1 2011
Event2011 IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting, APSURSI 2011 - Spokane, WA, United States
Duration: Jul 3 2011Jul 8 2011

Publication series

NameIEEE Antennas and Propagation Society, AP-S International Symposium (Digest)
ISSN (Print)1522-3965

Other

Other2011 IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting, APSURSI 2011
CountryUnited States
CitySpokane, WA
Period7/3/117/8/11

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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